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» Probabilistic Object Tracking Using Multiple Features
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ICCV
2007
IEEE
14 years 3 months ago
Non-Rigid Object Alignment with a Mismatch Template Based on Exhaustive Local Search
Non-rigid object alignment is especially challenging when only a single appearance template is available and target and template images fail to match. Two sources of discrepancy b...
Yang Wang, Simon Lucey, Jeffrey F. Cohn
CVPR
2011
IEEE
13 years 5 months ago
On Deep Generative Models with Applications to Recognition
The most popular way to use probabilistic models in vision is first to extract some descriptors of small image patches or object parts using well-engineered features, and then to...
Marc', Aurelio Ranzato, Joshua Susskind, Volodymyr...
TIP
2010
113views more  TIP 2010»
13 years 4 months ago
Multiplicative Noise Removal Using Variable Splitting and Constrained Optimization
Multiplicative noise (also known as speckle noise) models are central to the study of coherent imaging systems, such as synthetic aperture radar and sonar, and ultrasound and laser...
José M. Bioucas-Dias, Mário A. T. Fi...
ECCV
2010
Springer
14 years 1 months ago
Learning to Recognize Objects from Unseen Modalities
Abstract. In this paper we investigate the problem of exploiting multiple sources of information for object recognition tasks when additional modalities that are not present in the...
ICCV
2007
IEEE
13 years 11 months ago
COST: An Approach for Camera Selection and Multi-Object Inference Ordering in Dynamic Scenes
Development of multiple camera based vision systems for analysis of dynamic objects such as humans is challenging due to occlusions and similarity in the appearance of a person wi...
Abhinav Gupta, Anurag Mittal, Larry S. Davis